Analysis of Multiple Factors Influencing the Second-hand Car Pricing in China

Yuqing Liu; Siyi Song

doi:10.54097/ehss.v16i.9494

Authors

Yuqing Liu
Siyi Song

DOI:

https://doi.org/10.54097/ehss.v16i.9494

Keywords:

Second-hand cars, multiple linear regression, statistics, correlation, variables.

Abstract

This paper studies a formula to show the relationship between price of second-hand cars and different factors through multiple linear regression. As the expanding of second-hand car market, predicting an accurate price is essential for both sellers and buyers. Multiple linear regression can be used for predictive purposes since it uses multiple variables as predictors. The previous research has used the other methods to predict the price, like genetic algorithm or simple linear regression. The data here are all scraped from Che 300, one of the biggest websites for selling second-hand cars in China, and the qualitative variables are converted into weight to make the model simpler. Our results indicate that the price is predictable and several variables are unrelated. This study can set a reasonable price range or a certain price, and provide a reference to the owners or customers. Also, it is the application of data analysis in the field of machine learning.

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